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      <h1 class="entry-title">python3 nltk chapter 1</h1>
    <p class="meta">
<time datetime="2018-11-10T18:17:07+08:00" pubdate>2018-11-10 18:17:07</time>      
    </p>
</header>

    <div class="entry-content"><h1>语言处理与Python</h1>
<h3>1.语言计算：文本和单词</h3>
<h5>1.2 NLTK 入门</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">import</span> <span class="nn">nltk</span>
<span class="n">nltk</span><span class="o">.</span><span class="n">download</span><span class="p">()</span>
</code></pre></div>

<h5>1.3 搜索文本</h5>
<div class="highlight-custom"><pre><span></span><code>text1.concordance(&quot;monstrous&quot;)  # 搜索文本

text1.similar(&quot;monstrous&quot;)  # 查看相识上下文出现的单词

text2.common_contexts([&quot;monstrous&quot;, &quot;very&quot;])  # 查找两个词的共同上下文

text4.dispersion_plot([&quot;citizens&quot;, &quot;democracy&quot;, &quot;freedom&quot;, &quot;duties&quot;, &quot;America&quot;])  # 词汇分布图

len(set(text3)) / len(text3)  # 文本词汇丰富度
</code></pre></div>

<h5>1.3 布朗语料库</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">brown</span>
<span class="n">brown</span><span class="o">.</span><span class="n">categories</span><span class="p">()</span>
<span class="n">brown</span><span class="o">.</span><span class="n">words</span><span class="p">(</span><span class="n">categories</span><span class="o">=</span><span class="s1">&#39;news&#39;</span><span class="p">)</span>
<span class="n">brown</span><span class="o">.</span><span class="n">words</span><span class="p">(</span><span class="n">fileids</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;cg22&#39;</span><span class="p">])</span>
<span class="n">brown</span><span class="o">.</span><span class="n">sents</span><span class="p">(</span><span class="n">categories</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;news&#39;</span><span class="p">,</span> <span class="s1">&#39;editorial&#39;</span><span class="p">,</span> <span class="s1">&#39;reviews&#39;</span><span class="p">])</span>
</code></pre></div>

<h5>1.4 路透社语料库</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">reuters</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">fileids</span><span class="p">()</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">categories</span><span class="p">()</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">categories</span><span class="p">(</span><span class="s1">&#39;training/9865&#39;</span><span class="p">)</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">categories</span><span class="p">([</span><span class="s1">&#39;training/9865&#39;</span><span class="p">,</span> <span class="s1">&#39;training/9880&#39;</span><span class="p">])</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">fileids</span><span class="p">(</span><span class="s1">&#39;barley&#39;</span><span class="p">)</span>
<span class="n">reuters</span><span class="o">.</span><span class="n">fileids</span><span class="p">([</span><span class="s1">&#39;barley&#39;</span><span class="p">,</span> <span class="s1">&#39;corn&#39;</span><span class="p">])</span>
</code></pre></div>

<h5>1.5 就职演说语料库</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">inaugural</span>
<span class="n">inaugural</span><span class="o">.</span><span class="n">fileids</span><span class="p">()</span>
</code></pre></div>

<h5>1.6 标注文本语料库</h5>
<p>http://nltk.org/data
http://nltk.org/howto</p>
<h5>1.7 其他语言的语料库</h5>
<p>nltk.corpus.udhr  # 超过300种语言的世界人权宣言</p>
<h5>1.8 文本语料库的结构</h5>
<h6>NLTK 中定义的基本语料库函数, 使用help(nltk.corpus.reader)可以找到更多的文档</h6>
<div class="highlight-custom"><pre><span></span><code><span class="n">示例</span><span class="w">                       </span><span class="n">描述</span><span class="w">                          </span>
<span class="n">fileids</span><span class="p">()</span><span class="w">                  </span><span class="n">语料库中的文件</span><span class="w">                </span>
<span class="n">fileids</span><span class="p">(</span><span class="o">[</span><span class="n">categories</span><span class="o">]</span><span class="p">)</span><span class="w">      </span><span class="n">这些分类对应的语料库中的文件</span><span class="w">  </span>
<span class="n">categories</span><span class="p">()</span><span class="w">               </span><span class="n">语料库中的分类</span><span class="w">                </span>
<span class="n">categories</span><span class="p">(</span><span class="o">[</span><span class="n">fileids</span><span class="o">]</span><span class="p">)</span><span class="w">      </span><span class="n">这些文件对应的语料库中的分类</span><span class="w">  </span>
<span class="n">raw</span><span class="p">()</span><span class="w">                      </span><span class="n">语料库的原始内容</span><span class="w">              </span>
<span class="n">raw</span><span class="p">(</span><span class="n">fileids</span><span class="o">=[</span><span class="n">f1,f2,f3</span><span class="o">]</span><span class="p">)</span><span class="w">    </span><span class="n">指定文件的原始内容</span><span class="w">            </span>
<span class="n">raw</span><span class="p">(</span><span class="n">categories</span><span class="o">=[</span><span class="n">c1,c2</span><span class="o">]</span><span class="p">)</span><span class="w">    </span><span class="n">指定分类的原始内容</span><span class="w">            </span>
<span class="n">words</span><span class="p">()</span><span class="w">                    </span><span class="n">整个语料库中的词汇</span><span class="w">            </span>
<span class="n">words</span><span class="p">(</span><span class="n">fileids</span><span class="o">=[</span><span class="n">f1,f2,f3</span><span class="o">]</span><span class="p">)</span><span class="w">  </span><span class="n">指定文件中的词汇</span><span class="w">              </span>
<span class="n">words</span><span class="p">(</span><span class="n">categories</span><span class="o">=[</span><span class="n">c1,c2</span><span class="o">]</span><span class="p">)</span><span class="w">  </span><span class="n">指定分类中的词汇</span><span class="w">              </span>
<span class="n">sents</span><span class="p">()</span><span class="w">                    </span><span class="n">整个语料库中的句子</span><span class="w">            </span>
<span class="n">sents</span><span class="p">(</span><span class="n">fileids</span><span class="o">=[</span><span class="n">f1,f2,f3</span><span class="o">]</span><span class="p">)</span><span class="w">  </span><span class="n">指定文件中的句子</span><span class="w">              </span>
<span class="n">sents</span><span class="p">(</span><span class="n">categories</span><span class="o">=[</span><span class="n">c1,c2</span><span class="o">]</span><span class="p">)</span><span class="w">  </span><span class="n">指定分类中的句子</span><span class="w">              </span>
<span class="n">abspath</span><span class="p">(</span><span class="n">fileid</span><span class="p">)</span><span class="w">            </span><span class="n">指定文件在磁盘上的位置</span><span class="w">        </span>
<span class="n">encoding</span><span class="p">(</span><span class="n">fileid</span><span class="p">)</span><span class="w">           </span><span class="n">文件的编码</span><span class="err">（</span><span class="n">如果知道的话</span><span class="err">）</span><span class="w">    </span>
<span class="k">open</span><span class="p">(</span><span class="n">fileid</span><span class="p">)</span><span class="w">               </span><span class="n">打开指定语料库文件的文件流</span><span class="w">    </span>
<span class="n">root</span><span class="w">                       </span><span class="n">本地安装的语料库根目录的路径</span><span class="w">  </span>
<span class="n">readme</span><span class="p">()</span><span class="w">                   </span><span class="n">语料库的README文件的内容</span>
</code></pre></div>

<h5>1.9 加载你自己的语料库</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">PlaintextCorpusReader</span>
<span class="n">corpus_root</span> <span class="o">=</span> <span class="s1">&#39;/usr/share/dict&#39;</span> <span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">wordlists</span> <span class="o">=</span> <span class="n">PlaintextCorpusReader</span><span class="p">(</span><span class="n">corpus_root</span><span class="p">,</span> <span class="s1">&#39;.*&#39;</span><span class="p">)</span> <span class="p">[</span><span class="mi">2</span><span class="p">]</span>
<span class="n">wordlists</span><span class="o">.</span><span class="n">fileids</span><span class="p">()</span>
</code></pre></div>

<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">BracketParseCorpusReader</span>
<span class="n">corpus_root</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;C:\corpora\penntreebank\parsed\mrg\wsj&quot;</span> <span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">file_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;.*/wsj_.*\.mrg&quot;</span> <span class="p">[</span><span class="mi">2</span><span class="p">]</span>
<span class="n">ptb</span> <span class="o">=</span> <span class="n">BracketParseCorpusReader</span><span class="p">(</span><span class="n">corpus_root</span><span class="p">,</span> <span class="n">file_pattern</span><span class="p">)</span>
<span class="n">ptb</span><span class="o">.</span><span class="n">fileids</span><span class="p">()</span>
</code></pre></div>

<h3>2 条件频率分布</h3>
<h5>2.1 条件和事件</h5>
<h5>2.2 按文体计数词汇</h5>
<div class="highlight-custom"><pre><span></span><code><span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">brown</span>
<span class="n">cfd</span> <span class="o">=</span> <span class="n">nltk</span><span class="o">.</span><span class="n">ConditionalFreqDist</span><span class="p">(</span>
          <span class="p">(</span><span class="n">genre</span><span class="p">,</span> <span class="n">word</span><span class="p">)</span>
          <span class="k">for</span> <span class="n">genre</span> <span class="ow">in</span> <span class="n">brown</span><span class="o">.</span><span class="n">categories</span><span class="p">()</span>
          <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">brown</span><span class="o">.</span><span class="n">words</span><span class="p">(</span><span class="n">categories</span><span class="o">=</span><span class="n">genre</span><span class="p">))</span>

<span class="n">cfd</span>  <span class="c1"># &lt;ConditionalFreqDist with 2 conditions&gt;</span>
<span class="n">cfd</span><span class="o">.</span><span class="n">conditions</span><span class="p">()</span>  <span class="c1"># [&#39;news&#39;, &#39;romance&#39;]</span>

<span class="nb">print</span><span class="p">(</span><span class="n">cfd</span><span class="p">[</span><span class="s1">&#39;news&#39;</span><span class="p">])</span>
<span class="c1"># &lt;FreqDist with 14394 samples and 100554 outcomes&gt;</span>

<span class="nb">print</span><span class="p">(</span><span class="n">cfd</span><span class="p">[</span><span class="s1">&#39;romance&#39;</span><span class="p">])</span>
<span class="o">&lt;</span><span class="n">FreqDist</span> <span class="k">with</span> <span class="mi">8452</span> <span class="n">samples</span> <span class="ow">and</span> <span class="mi">70022</span> <span class="n">outcomes</span><span class="o">&gt;</span>

<span class="n">cfd</span><span class="p">[</span><span class="s1">&#39;romance&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">most_common</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>

<span class="n">cfd</span><span class="p">[</span><span class="s1">&#39;romance&#39;</span><span class="p">][</span><span class="s1">&#39;could&#39;</span><span class="p">]</span>
<span class="c1"># 193</span>
</code></pre></div>

<h5>2.3 绘制分布图和分布表</h5>
<div class="highlight-custom"><pre><span></span><code>cfd.tabulate(conditions=[&#39;English&#39;, &#39;German_Deutsch&#39;],
             samples=range(10), cumulative=True)

cfd.plot(conditions=[&#39;English&#39;, &#39;German_Deutsch&#39;],
         samples=range(10), cumulative=True)
</code></pre></div>

<h5>2.4 使用双连词生成随机文本</h5>
<p>条件频率分布是一个对许多NLP 任务都有用的数据结构。2.1总结了它们常用的方法。</p>
<div class="highlight-custom"><pre><span></span><code><span class="n">示例</span><span class="w">                                 </span><span class="n">描述</span>
<span class="n">cfdist</span><span class="o">=</span><span class="n">ConditionalFreqDist</span><span class="p">(</span><span class="n">pairs</span><span class="p">)</span><span class="w">    </span><span class="n">从配对列表中创建条件频率分布</span><span class="w">                       </span>
<span class="n">cfdist</span><span class="p">.</span><span class="n">conditions</span><span class="p">()</span><span class="w">                  </span><span class="n">条件</span>
<span class="n">cfdist</span><span class="o">[</span><span class="n">condition</span><span class="o">]</span><span class="w">                    </span><span class="n">此条件下的频率分布</span>
<span class="n">cfdist</span><span class="o">[</span><span class="n">condition</span><span class="o">][</span><span class="n">sample</span><span class="o">]</span><span class="w">            </span><span class="n">此条件下给定样本的频率</span>
<span class="n">cfdist</span><span class="p">.</span><span class="n">tabulate</span><span class="p">()</span><span class="w">                    </span><span class="n">为条件频率分布制表</span>
<span class="n">cfdist</span><span class="p">.</span><span class="n">tabulate</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span><span class="n">conditions</span><span class="p">)</span><span class="w">  </span><span class="n">指定样本和条件限制下制表</span>
<span class="n">cfdist</span><span class="p">.</span><span class="n">plot</span><span class="p">()</span><span class="w">                        </span><span class="n">为条件频率分布绘图</span>
<span class="n">cfdist</span><span class="p">.</span><span class="n">plot</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span><span class="n">conditions</span><span class="p">)</span><span class="w">      </span><span class="n">指定样本和条件限制下绘图</span>
<span class="n">cfdist1</span><span class="o">&lt;</span><span class="n">cfdist2</span><span class="w">                      </span><span class="n">测试样本在cfdist1中出现次数是否小于在cfdist2中出现次数</span>
</code></pre></div>

<h3>3 更多关于Python：代码重用</h3>
<h3>4 词汇资源</h3></div>
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